Summary

This project seeks to improve on the Howard et al. (2020) methods used to estimate sport fish harvest, catches and releases of rockfish in Alaska waters. This is essentially a Bayesian version of the Howard methods that allows for more appropriate and defensible sharing of information between areas, handles missing data in a more appropriate manor, accurately propagates uncertainty throughout the estimation procedure and thus does not rely on the decision tree approach in the original Howard methods. Furthermore, the Bayesian approach should provide sport fish harvest, catch and mortality estimates back to 1978 when the SWHS was implemented. Harvest estimates should be mostly consistent with Howard estimates during contemporary times, but may differ based on more appropriate weighting of SWHS and logbook data, including estimating and correcting bias in the SWHS data. Furthermore, the Howard methods are wholly reliant on logbook release estimates and ignore the release estimates from the SWHS data (inferred from the catch and harvest estimates). Here we explore several models that attempt to balance all of the data in estimating releases.

Data

Harvest data was available for 22 commercial fishing management areas in Southcentral and Southeast Alaska. Areas with negligible rockfish harvest were pooled with adjacent areas for analysis. Specifically the Aleutian and Bering areas were pooled into an area labeled BSAI; the IBS and EKYT were pooled into an area labeled EKYKT; the Southeast, Southwest, SAKPEN and Chignik areas were pooled into an area labeled SOKO2PEN and the Westside and Mainland areas were pooled into an area labeled WKMA.

Stateside Harvest Survey (SWHS)

Statewide harvest survey estimates of rockfish catch and harvest are available for 28 years (1996-2023) for all users and for 13 years (2011-2023) for guided anglers (Figure 0). Additionally, there are estimates from 1977- 1995 that required some partitioning work to ascribe to current management units. Harvests in unknown areas were apportioned based on harvest proportions in 1996. Variance estimates are not available for pre-1996 data and as such, the maximum observed coefficient of variation (cv) in each commercial fisheries management unit was applied.

**Figure 0.**- Data sources for estimating rockfish harvests and releases in ADF&G commercial fisheries management units.

Figure 0.- Data sources for estimating rockfish harvests and releases in ADF&G commercial fisheries management units.


SWHS estimates are believed to be biased to some degree. These modelling efforts aim to estimate and correct for that bias with the assumption that logbook harvests are a census of guided harvests.

Rockfish release estimates are inferred from the difference between catch and harvest estimates.

Adam noted that the first 5 years (23 years counting the historical data) in the SWHS data set for PWSO seem unreasonable (close to zero and not corroborated with logbook estimates). Adam recommended setting these harvests to unknown, but current model development has included the data. Once a satisfactory model has been identified we will exam the effects of censoring the PWSO data.

Creel Surveys

NA

Guide Logbooks

Sport fishing guides were required to report their harvest of rockfish for 26 years (1998-2023). Reported harvest is also available by assemblage (pelagic vs. non-pelagic). Harvest of yelloweye rockfish were reported separately beginning in 2006.

Logbooks also record the number of rockfish released for the same categories. However, the reliability of the release data is somewhat questionable as reported releases are generally far lower than that estimated by the SWHS. As such several treatments of the data are considered.

Logbook versus SWHS estimates

Estimates of guided harvests and releases from the SWHS do not align with the census from charter logbooks. Logbook harvest reports are generally considered reliable and are used to assess the bias in SWHS reports. However, there is even greater disparity between release estimates in the two sources and it is debatable whether logbook releases should be treated as a census. The Howard et al. (2020) methods do treat the logbook release data as “true” and thus are considerably less than would be estimated from the SWHS data.

**Figure 1.**- SWHS harvest estimates from guided trips (Hhat) versus repoted harvests from charter logbooks (H_lb).

Figure 1.- SWHS harvest estimates from guided trips (Hhat) versus repoted harvests from charter logbooks (H_lb).


The Howard methods treat the logbook release data as a census and then use the ratio of guided:unguided releases in the SWHS to expand the logbook release estimates to generate total and unguided estimates.

To evaluate this discrepancy, several models were used to estimate releases in this exploration. One method (\(LB_{fit}\)) considers the logbook release data to be reliable and a second method (\(LB_{cens}\)) treats the logbook release data as estimates of the minimum released, thus giving more weight to SWHS release estimates. A third method (\(LB_{hyb}\)) is a hybrid approach that treats reported releases of yelloweye as reliable but total rockfish and pelagic rockfish releases as minimums. Model development to date has revealed a tension between the total and pelagic logbook releases and the yelloweye logbook releases.

Composition data

Harvest sampling data exists from Gulf of Alaska areas since 1996 and from Southeast Alaska areas since 2006. Port sampling data is comprised of the number of total rockfish, pelagic and non-pelagic rockfish, black rockfish and yelloweye rockfish.

A current challenge at this juncture is how to accommodate the prohibition on retaining yelloweye in Southeast from 2020 through 2024. Because it is closed to retention the port sampling data is not reflective of releases while remaining an accurate description of the harvest. Current modelling efforts revolve around developing a separate yelloweye curve that censors the missing data.

Process equations

The true harvest \(H_{ay}\) of rockfish for area \(a\) during year \(y\) is assumed to follow a temporal trend defined by a penalized spline:

\[\begin{equation} \textrm{log}(H_{ay})~\sim~\textrm{Normal}(f(a,y), {\sigma_H}) \end{equation}\]

where \(f(a,y)\) in a p-spline basis with 7 components (knots) and a second degree penalty. The variance, \(\sigma_H\), was given a normal prior with a mean and standard deviation of 0.25 and 1, respectively.

Charter and private harvest \(H_{ayu}\) (where u = 1 for charter anglers and u = 2 for private anglers) is a fraction of total annual harvest in each area:

\[\begin{equation} H_{ay1}~=~H_{ay}P_{(user)ay1}\\H_{ay2}~=~H_{ay}(1-P_{(user)ay1}) \end{equation}\]

where \(P_{(user)ay1}\) is the fraction of the annual harvest in each area taken by charter anglers. \(P_{(user)ay1}\) was modeled hierarchically across years as:

\[\begin{equation} P_{(user)ay1}~\sim~\textrm{beta}(\lambda1_a, \lambda2_a) \end{equation}\]

with non-informative priors on both parameters.

Annual black rockfish harvest \(H_{(black)ayu}\) for each area and user group is:

\[\begin{equation} H_{(black)ayu}~=~H_{ayu}P_{(pelagic)ayu}P_{(black|pelagic)ayu} \end{equation}\]

where \(P_{(pelagic)ayu}\) is the fraction of the annual harvest for each area and user group that was pelagic rockfish and \(P_{(black|pelagic)ayu}\) is the fraction of the annual harvest of pelagic rockfish for each area and user group that was black rockfish. Annual yelloweye rockfish harvest \(H_{(yelloweye)ayu}\) for each area and user group:

\[\begin{equation} H_{(yelloweye)ayu}~=~H_{ayu}(1-P_{(pelagic)ayu})P_{(yelloweye|non-pelagic)ayu} \end{equation}\]

where \(P_{(yellow|non-pelagic)ayu}\) is the fraction of the annual harvest of non-pelagic rockfish for each area and user group that was yelloweye rockfish. The composition parameters (\(P_{(pelagic)ayu}\), \(P_{(black|pelagic)ayu}\), \(P_{(yelloweye|non-pelagic)ayu}\)) were modeled using a logistic curve that would allow hindcasting without extrapolating beyond the limit of observed values such that:

\[\begin{equation} \textrm{logit}(P_{(comp)ayu})~=~\beta1_{(comp)ayu} + \frac{\beta2_{(comp)ayu}}{(1 + exp(\beta3_{(comp)ayu}*(y - \beta4_{(comp)ayu})))} + \beta5_{(comp)ayu}*I(u=private)+re_{(comp)ayu} \end{equation}\]

where the \(\beta\) parameters define the intercept, scaling factor, slope, inflection point and private angler effect, respectively, \(y\) is the year index, \(I(u=private)\) is an index variable which is 1 when the user groups is private and 0 otherwise and \(re_{(comp)ayu}\) is a random effect with a non-informative prior.

The true number of released rockfish \(R_{ayu}\) were based on the proportion of the total catch harvested by area, year, user group and species grouping (pelagic or yelloweye), \(pH_{(comp)ayu}\). Thus, converting \(H_{(comp)ayu}\) to total catches by user group, \(C_{(comp)ayu}\), with \(pH_{(comp)ayu}\) results in estimates of total releases such that

\[\begin{equation} R_{(comp)ayu}~=~ C_{(comp)ayu} - H_{(comp)ayu} ~=~ \frac{H_{(comp)ayu}}{pH_{(comp)ayu}} - H_{(comp)ayu} \end{equation}\]

with total releases calculated from the sum of the user group releases. The proportion of total rockfish harvested by user group, \(pH_{ayu}\), was assumed to be the mean of \(pH_{(pelagic)ayu}\), \(pH_{(yelloweye)ayu}\) and \(pH_{(nonpel-nonYE)ayu}\) weighted by the relative harvest \(H_{(comp)ayu}\) such that

\[\begin{equation} R_{ayu}~=~ \frac{\sum ({H_{(comp)ayu} * pH_{(comp)ayu})}}{\sum {H_{(comp)ayu}}} \end{equation}\]

The proportion harvest parameters \(pH_{(comp)ayu}\) were modeled using a logistic curve that would allow hindcasting based on trends in the data without extrapolating beyond the range of observed values such that

\[\begin{equation} \textrm{logit}(pH_{ayuc})~=~\beta1_{(pH)ayuc} + \frac{\beta2_{(pH)ayuc}}{(1 + exp(\beta3_{(pH)ayuc}*(y - \beta4_{(pH)ayuc}))) + \beta34_{(pH)ayuc}} \end{equation}\]

A random effect term allowed estimation during the historical period when data is available, but the curve defined by the above equation determined release estimates between 1977 and 1990.

Observation equations

SWHS estimates of annual rockfish harvest \(\widehat{SWHS}_H{ay}\) were assumed to index true harvest:

\[\begin{equation} \widehat{SWHS}_H{ay}~\sim~\textrm{LogNormal}\left(\textrm{log}(H_{ay}b_{ay}), \sigma_{SWHSHay}^2\right) \end{equation}\]

where bias in the SWHS harvest estimates \(b_H{ay}\) is modeled hierarchically across years as:

\[\begin{equation} b_H{ay}~\sim~\textrm{Normal}(\mu_H{(b)a}, \sigma_H{(b)a}) \end{equation}\]

with non-informative priors on both parameters.

SWHS estimates of guided angler harvest \(\widehat{SWHS}_H{ay1}\) are related to total harvest by:

\[\begin{equation} \widehat{SWHS}_H{ay1}~\sim~\textrm{LogNormal}\left(\textrm{log}(H_{ay1}b_{ay}), \sigma_{SWHS_{ay1}}^2\right) \end{equation}\]

Reported guide logbook harvest \(\widehat{LB}_H{ay}\) is related to true harvest as:

\[\begin{equation} \widehat{LB}_H{ay}~\sim~\textrm{Poisson}(H_{ay1})\\ \widehat{LB}_H{(pelagic)ay}~\sim~\textrm{Poisson}(H_{ay1}P_{(pelagic)ay1})\\ \widehat{LB}_H{(yelloweye)ay}~\sim~\textrm{Poisson}(H_{(yelloweye)ay1})\\ \end{equation}\]

SWHS estimates of annual rockfish releases \(\widehat{SWHS}_R{ay}\) were assumed to index true releases in a similar fashion and thus modeled similarly. Because logbook release data is more questionable and demonstrates greater disagreement with SWHS estimates (Figure 1), several approaches have been explored. In the first approach model \(LB_{fit}\) treats the release data as a true census and the releases are related to true releases just as harvests were modelled such that:

\[\begin{equation} \widehat{LB}_R{ay}~\sim~\textrm{Poisson}(R_{ay1})\\ \widehat{LB}_R{(pelagic)ay}~\sim~\textrm{Poisson}(R_{ay1}P_{(pelagic)ay1})\\ \widehat{LB}_R{(yelloweye)ay}~\sim~\textrm{Poisson}(R_{(yelloweye)ay1})\\ \end{equation}\]

In the second approach we consider the logbook release data to be a minimal estimate of the true releases. Thus model \(LB_{cens}\) censors the release data (censored data is entered as NA) and treats the reported releases as a minimal number such that

\[\begin{equation} \text{censored} \widehat{LB}_R{ay}~\sim~\textrm{LogNormal}\left(\log(R_{ay}), 1\right)\text{T}\left(\widehat{LB}_R{ay}, \infty\right)\\ \text{censored} \widehat{LB}_R{(pelagic)ay}~\sim~\textrm{LogNormal}\left(\log(R_{(pelagic)ay}), 1\right)\text{T}\left(\widehat{LB}_R{(pelagic)ay}, \infty\right)\\ \text{censored} \widehat{LB}_R{(ye)ay}~\sim~\textrm{LogNormal}\left(\log(R_{(ye)ay}), 1\right)\text{T}\left(\widehat{LB}_R{(ye)ay}, \infty\right)\\ \end{equation}\]

Model \(LB_{hyb}\) is a hybrid approach that treats the yelloweye releases as a reliable census of yelloweye releases (given the emphasis and ease of recording these fish) but censors the pelagic and total rockfish release estimates such that

\[\begin{equation} \text{censored} \widehat{LB}_R{ay}~\sim~\textrm{LogNormal}\left(\log(R_{ay}), 1\right)\text{T}\left(\widehat{LB}_R{ay}, \infty\right) \\ \text{censored} \widehat{LB}_R{(pelagic)ay}~\sim~\textrm{LogNormal}\left(\log(R_{(pelagic)ay}), 1\right)\text{T}\left(\widehat{LB}_R{(pelagic)ay}, \infty\right) \\ \widehat{LB}_R{(yelloweye)ay}~\sim~\textrm{Poisson}(R_{(yelloweye)ay1})\\ \end{equation}\]

SWHS estimates of guided angler release \(\widehat{SWHS}_R{ay1}\) is modeled the same as harvests.

SWHS release bias was modeled differently in the \(LB_{fit}\), \(LB_{cens}\), and \(LB_{hyb}\) models. Because the \(LB_{fit}\) model assumes that logbook release data is true and the poison likelihoods assume a much smaller variance than the large variances associated with the SWHS release estimates, SWHS release estimates \(b_R{ay}\) were modelled independently of the harvest bias \(b_H{ay}\) such that

\[\begin{equation} b_R{ay}~\sim~\textrm{Normal}(\mu_R{(b)a}, \sigma_R{(b)a}) \end{equation}\]

where bias in the SWHS release estimates \(b_R{ay}\) is modeled hierarchically across years as:

\[\begin{equation} b_R{ay}~\sim~\textrm{Normal}(\mu_R{(b)a}, \sigma_R{(b)a}) \end{equation}\]

with non-informative priors on both parameters.

The \(LB_{cens}\) model treats the logbook release data as lower bound on the release estimates and thus the likelihood linking true releases to the SWHS release estimates is dominant. During model development it was apparent that estimating bias in the SWHS data was more difficult and a different structure was employed that assumed bias in SWHS release data followed a similar pattern to that of the harvests but is offset by some area specific amount. In these models \(b_R{ay}\) differed from \(b_H{ay}\) by offset \(Rboff_{a}\) such that

\[\begin{equation} b_R{ay}~=~b_H{ay} + Rboff_{ay} \end{equation}\]

where

\[\begin{equation} Rboff_{a}~\sim~\textrm{Normal}(\mu_{(bR)r}, \sigma_{(bR)r}) \end{equation}\]

such that \(Rboff_{a}\) was modeled hierarchically across region r.

The number of pelagic rockfish sampled in harvest sampling programs \(x_{(pelagic)ayu}\) follow a binomial distribution:

\[\begin{equation} x_{(pelagic)ayu}~\sim~\textrm{Binomial}(P_{(pelagic)ayu}, N_{ayu}) \end{equation}\]

where \(N_{ayu}\) is the total number of rockfish sampled in area \(a\) during year \(y\) form user group \(u\). The number of black rockfish sampled in harvest sampling programs and the number of yellow rockfish sampled modeled analogously with an appropriately substituted \(N\).

Unresolved issues and outstanding questions:

Models detailed in this markdown represent the next step in the modelling process whereby the pH parameters are separated out by species. This approach separates the compositional data that is germaine to the harvests from the release estimates and releases are now based on pH. Additionally, this approach allows the pH parameters to differ between pelagic and yelloweye which is appropriate given regulatory changes as well as fisherman and industry behaviour and is born out in the results. The approach results in great uncertainty around unguided release estimates, but that uncertainty is appropriate given the data. These models handle the yelloweye closures in southeast much more appropriately given that the compositional data is no longer directly applied to the release estimates. These versions of the model are in development and it is unclear whether the \(LB_{cens}\) model would work, but it appears applicable to the \(LB_{fit}\) and \(LB_{hyb}\) approaches.

Other issues include:

  1. Complete convergence has not been achieved and the logistic curve parameters for p_pelagic and p_yellow remain the last sticking point. I think that p_pelagic will resolve with longer chains.
  2. Estimate precision: These models are producing more precise harvest estimates that in Adam’s original model. I am not sure why at this juncture. sigma_H on the spline was switched from a fixed value to a prior centered around that fixed value, but the model estimates are in the same range as the fixed value. Would the number of knots in the spline explain this? 7 knots was settled on during early model fitting when it clearly performed better than fewer or more knots.
  3. Prior choices in general need to be vetted. The priors on the logistic curves are fairly informed in an effort to achieve the desired shapes for hindcasting. Ideally, sensitivity testing would occur but the model is very slow to converge. The beta parameters on the logistic curves have required a lot of work on the priors to reach convergence.
  4. Random effects on pH: These are currently used in the model but because pH isn’t linked to data as the p_comp data is I am not sure what to make of them or if they are appropriate.
  5. Model comparisons: I need to write code for comparing models side by side as well as quantifying the differences between these methods and the Howard methods.

Results

**Figure X.**- Rhat values and proportion of parameters that converged (Rhat < 1.1.)

Figure X.- Rhat values and proportion of parameters that converged (Rhat < 1.1.)

Estimate comparison

Since previous estimates of rockfish harvest have been produced these first 3 graphs will be used to show how the modeled estimates compare to the estimates produced earlier. For total rockfish the estimates are in general agreement although differences are noted. These estimates should be more reliable because they include both SWHS and guide logbook data, handle variance more appropriately, use hierarchical distributions when data is missing, directly consider observation error and are produced using reproducible research.

**Figure 2.**- Total rockfish harvests 1996--2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 2.- Total rockfish harvests 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.



**Figure 3.**- Total rockfish releases 1996--2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 3.- Total rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.


Notes from Adam: When looking at only black rockfish the most significant differences are for the Prince William Sound Inside area. I did not spend a great deal of time tracking this down although it looks like the previous version used bad values for \(P_{(black)ayu}\) for at least unguided anglers. For the moment I would ignore the results for BSIA and SOKO2SAP. I think it is possible to give approximate values for these areas but it will require a little more coding which I have yet to do.

**Figure 4.**- Black rockfish harvests 1996--2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 4.- Black rockfish harvests 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.


And black rockfish releases…

**Figure 5.**- Black rockfish releases 1996--2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 5.- Black rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.



**Figure 6.**- Yellow rockfish harvests 1996--2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 6.- Yellow rockfish harvests 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.



**Figure 7.**- Yellow rockfish releases 1996--2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Figure 7.- Yellow rockfish releases 1996–2023. Lines and error polygons represent model estimates and points and error bars represent Howard et al estimates.

Model fit

Logbook residuals

**Figure 8.**- Residuals from logbook harvests

Figure 8.- Residuals from logbook harvests


SWHS residuals

**Figure 9.**- Residuals from SWHS harvests.

Figure 9.- Residuals from SWHS harvests.



**Figure 10.**- Residual of SWHS releases

Figure 10.- Residual of SWHS releases

Parameter estimates

P(Charter)

These histograms show the posterior distribution of the mean percent of rockfish harvested by the charter fleet.

**Figure 11.**- Mean percent of harvest by charter anglers.

Figure 11.- Mean percent of harvest by charter anglers.


When considered annually we see the percent of rockfish harvested by the charter fleet follows our data fairly well although we just do not have much information about this ratio. Prior to 2011 the percent charter is confounded with SWHS bias and should be mostly discounted.

**Figure 12.**- Annual estimates of the percent of harvest by charter anglers for 16 commerical fishing manamgent areas, 1996-2023.

Figure 12.- Annual estimates of the percent of harvest by charter anglers for 16 commerical fishing manamgent areas, 1996-2023.

P(Harvest)

These plots show the fitted logistic line to the proportion of caught rockfish that are harvested. These estimates are used for hindcasting catch estimates based on the harvest data in early years when catch estimates are unavailable.

**Figure 13.**- Annual proportion of all rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

Figure 13.- Annual proportion of all rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.


**Figure 13.**- Annual proportion of pelagic rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

Figure 13.- Annual proportion of pelagic rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.


**Figure 13.**- Annual proportion of yelloweye rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

Figure 13.- Annual proportion of yelloweye rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.


**Figure 13.**- Annual proportion of non-pelagic, non-yelloweye rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

Figure 13.- Annual proportion of non-pelagic, non-yelloweye rockfish catch that was harvested. Note that pre-1990 estimates are used to estimate catch in these years when catch estimates are not available.

SWHS bias

Figure 14 shows the mean estimate for SWHS bias. Cook Inlet, North Gulf Coast and North Southeast Inside all look pretty good while most other areas have substantial bias. Prince William Sound Inside has the largest bias.

**Figure 14.**- Mean SWHS bias for harvests and catches. Note that a bias < 1 indicates that the SWHS *underestimates* the true value and bias > 1 indicates the survey *overestimates* the true value.

Figure 14.- Mean SWHS bias for harvests and catches. Note that a bias < 1 indicates that the SWHS underestimates the true value and bias > 1 indicates the survey overestimates the true value.


Our estimates of SWHS bias track observations fairly well when he have guided harvest estimates. There are some disturbing trends/patterns seen in the earlier time periods. Often the patterns represent periods where SWHS estimates and guide logbook estimates do not follow the recent relationship. I’m not sure what drives the trends but it seems plausible to me that long-term changes in the ratio of charter and private anglers may be a factor. If Charter/Private ratio information is available in the historical creel data it my be helpful here (particularly for North Southeast Inside and South Southeast outside).

**Figure 15.**- Annual estimates of SWHS bias in harvests and releases for 16 commerical fishing manamgent areas, 1996-2023. Note that a bias < 1 indicates that the SWHS *underestimates* the true value and bias > 1 indicates the survey *overestimates* the true value.

Figure 15.- Annual estimates of SWHS bias in harvests and releases for 16 commerical fishing manamgent areas, 1996-2023. Note that a bias < 1 indicates that the SWHS underestimates the true value and bias > 1 indicates the survey overestimates the true value.

P(pelagic)

We model the percentage of pelagic rockfish in the harvest because we have the information for charter anglers (via logbooks) starting in 1998. Other than looking at the model estimates you can use Figure 8 to compare the two data streams for pelagic rockfish harvest. In general they are in agreement with major exceptions in Price William Sound inside, Prince William Sound outside (early in the time series) and South Southeast inside.

**Figure 16.**- Annual estimates of the percent of the sport harvest that was pelagic rockfish for 16 commerical fishing manamgent areas, 1996-2023.

Figure 16.- Annual estimates of the percent of the sport harvest that was pelagic rockfish for 16 commerical fishing manamgent areas, 1996-2023.

P(black|pelagic)

Note that in Southeast Alaska we only have composition data starting in 2006. Tania dug up old SE data, but it did not provide any useful data for species apportionment.

**Figure 17.**- Annual estimates of the percent of the sport harvest of pelagic rockfish that were black rockfish for 16 commerical fishing manamgent areas, 1996-2023.

Figure 17.- Annual estimates of the percent of the sport harvest of pelagic rockfish that were black rockfish for 16 commerical fishing manamgent areas, 1996-2023.

P(yelloweye|non-pelagic)

**Figure 18.**- Annual estimates of the percent of the sport harvest of non-pelagic rockfish that were yelloweye rockfish for 16 commerical fishing manamgent areas, 1996-2023.

Figure 18.- Annual estimates of the percent of the sport harvest of non-pelagic rockfish that were yelloweye rockfish for 16 commerical fishing manamgent areas, 1996-2023.



Summary of unconverged parameters:

Table 1. Summary of unconverged parameters including the number (n) and the average Rhat from the unconverged parameters.
parameter n badRhat_avg
beta3_yellow 2 43.361291
beta1_yellow 2 3.969968
sd_comp 1 3.732383
beta2_yellow 4 3.239542
beta3_pH 15 2.681527
beta4_yellow 1 2.176994
beta2_pH 8 2.085984
beta1_pH 11 1.916997
mu_beta0_pH 2 1.526047
beta0_pH 11 1.505999
parameter n badRhat_avg
beta1_pelagic 3 1.230565
beta0_pelagic 3 1.216110
tau_beta0_yellow 2 1.206807
beta0_yellow 1 1.183236
tau_beta0_black 1 1.168028
beta2_pelagic 4 1.166255
tau_beta0_pelagic 1 1.153900
tau_beta0_pH 2 1.143343
beta0_black 3 1.128891
beta3_pelagic 1 1.125145
Table 2. Summary of unconverged parameters by area
afognak BSAI CI CSEO eastside EWYKT NG NSEI NSEO PWSI PWSO SOKO2SAP SSEI SSEO WKMA
beta0_black 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1
beta0_pelagic 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0
beta0_pH 0 0 1 1 1 1 0 1 1 1 1 1 1 1 0
beta0_yellow 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
beta1_pelagic 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0
beta1_pH 0 0 1 1 0 1 0 1 1 1 0 0 1 1 0
beta1_yellow 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0
beta2_pelagic 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1
beta2_pH 0 0 1 1 0 1 0 1 0 0 0 0 1 1 0
beta2_yellow 0 0 0 1 0 1 1 0 0 0 1 0 0 0 0
beta3_pelagic 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
beta3_pH 0 0 1 1 1 1 0 1 1 1 1 1 1 1 0
beta3_yellow 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0
beta4_yellow 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
mu_beta0_pH 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0
sd_comp 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
tau_beta0_black 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
tau_beta0_pelagic 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
tau_beta0_pH 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0
tau_beta0_yellow 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0

Parameter estimates:

Summary Table of Parameter Estimates
Parameter mean sd Lower_CI Median Upper_CI
mu_bc_H[1] -0.158 0.069 -0.288 -0.159 -0.020
mu_bc_H[2] -0.120 0.037 -0.188 -0.122 -0.041
mu_bc_H[3] -0.462 0.069 -0.598 -0.463 -0.325
mu_bc_H[4] -1.184 0.223 -1.634 -1.178 -0.754
mu_bc_H[5] 0.582 0.648 -0.310 0.473 2.178
mu_bc_H[6] -2.230 0.321 -2.840 -2.238 -1.594
mu_bc_H[7] -0.483 0.113 -0.714 -0.480 -0.266
mu_bc_H[8] 0.145 0.373 -0.481 0.115 0.952
mu_bc_H[9] -0.328 0.132 -0.582 -0.327 -0.068
mu_bc_H[10] -0.127 0.067 -0.251 -0.127 0.008
mu_bc_H[11] -0.131 0.035 -0.199 -0.132 -0.061
mu_bc_H[12] -0.270 0.109 -0.504 -0.261 -0.068
mu_bc_H[13] -0.152 0.078 -0.304 -0.152 0.007
mu_bc_H[14] -0.329 0.098 -0.529 -0.328 -0.141
mu_bc_H[15] -0.361 0.046 -0.450 -0.362 -0.265
mu_bc_H[16] -0.295 0.374 -0.931 -0.321 0.506
mu_bc_R[1] 1.721 0.857 -0.241 1.828 3.080
mu_bc_R[2] 1.074 0.750 -0.385 1.095 2.415
mu_bc_R[3] 1.362 0.717 -0.288 1.471 2.427
mu_bc_R[4] -0.179 1.034 -2.277 -0.162 1.839
mu_bc_R[5] 1.738 1.018 0.006 1.615 4.171
mu_bc_R[6] 0.723 0.593 -0.599 0.778 1.759
mu_bc_R[7] 1.611 1.207 -1.420 1.889 3.106
mu_bc_R[8] 2.091 0.710 0.207 2.215 3.150
mu_bc_R[9] 2.373 1.152 -0.453 2.524 4.031
mu_bc_R[10] 2.133 1.368 -0.815 2.178 4.404
mu_bc_R[11] 0.850 0.537 -0.347 0.975 1.665
mu_bc_R[12] -0.516 0.556 -1.625 -0.518 0.560
mu_bc_R[13] 0.478 0.378 -0.314 0.498 1.209
mu_bc_R[14] 0.573 0.379 -0.181 0.573 1.326
mu_bc_R[15] 0.443 0.257 -0.098 0.445 0.920
mu_bc_R[16] 1.030 0.485 -0.138 1.109 1.797
tau_pH[1] 40389.337 405934.607 75.342 919.948 187692.069
tau_pH[2] 1.945 1.020 0.479 2.402 3.263
tau_pH[3] 3.304 0.511 2.113 3.322 4.272
beta0_pH[1,1] 1.711 1.099 -0.764 1.778 3.633
beta0_pH[2,1] 1.880 0.923 0.131 1.843 3.680
beta0_pH[3,1] 1.884 1.075 -0.365 1.923 3.757
beta0_pH[4,1] 1.565 1.428 -1.773 1.692 3.902
beta0_pH[5,1] 2.431 1.906 -0.276 2.212 6.189
beta0_pH[6,1] 2.963 2.544 -0.088 2.426 8.275
beta0_pH[7,1] 2.648 2.756 -1.223 2.470 7.486
beta0_pH[8,1] 1.519 1.125 -1.112 1.575 3.736
beta0_pH[9,1] 2.319 1.720 -1.169 2.235 5.427
beta0_pH[10,1] 2.205 1.492 -0.925 2.196 4.931
beta0_pH[11,1] -0.924 0.620 -2.247 -0.908 0.210
beta0_pH[12,1] -0.911 0.672 -2.313 -0.897 0.335
beta0_pH[13,1] -0.929 0.616 -2.187 -0.912 0.298
beta0_pH[14,1] -0.962 0.705 -2.460 -0.937 0.304
beta0_pH[15,1] -1.062 0.620 -2.386 -1.012 0.007
beta0_pH[16,1] -1.070 0.671 -2.561 -1.023 0.114
beta0_pH[1,2] 2.492 0.322 1.935 2.462 3.170
beta0_pH[2,2] 2.689 0.347 1.865 2.744 3.221
beta0_pH[3,2] 2.479 0.374 1.771 2.451 3.244
beta0_pH[4,2] 2.545 0.353 1.872 2.595 3.128
beta0_pH[5,2] 3.182 1.171 1.552 2.965 5.799
beta0_pH[6,2] 2.741 0.389 2.055 2.728 3.533
beta0_pH[7,2] 1.761 0.837 -1.330 1.929 2.541
beta0_pH[8,2] 2.608 0.564 1.137 2.725 3.243
beta0_pH[9,2] 2.736 0.594 1.680 2.678 3.918
beta0_pH[10,2] 2.953 0.802 1.201 3.034 4.124
beta0_pH[11,2] -4.420 0.595 -5.310 -4.558 -3.056
beta0_pH[12,2] -4.470 0.597 -5.613 -4.509 -3.237
beta0_pH[13,2] -4.290 0.500 -5.178 -4.330 -3.220
beta0_pH[14,2] -5.040 0.694 -6.216 -5.131 -3.621
beta0_pH[15,2] -4.050 0.412 -4.774 -4.070 -3.157
beta0_pH[16,2] -4.204 0.701 -5.107 -4.327 -2.188
beta0_pH[1,3] 1.172 0.273 0.637 1.194 1.622
beta0_pH[2,3] 1.535 0.591 0.069 1.606 2.381
beta0_pH[3,3] 1.901 0.406 1.006 1.929 2.666
beta0_pH[4,3] 1.875 0.727 0.380 1.822 3.012
beta0_pH[5,3] 0.278 0.710 -1.172 0.345 1.359
beta0_pH[6,3] 0.061 0.900 -2.035 0.242 0.943
beta0_pH[7,3] 0.327 0.566 -0.957 0.438 0.901
beta0_pH[8,3] 0.304 0.203 -0.103 0.311 0.681
beta0_pH[9,3] 0.348 0.417 -0.519 0.378 1.085
beta0_pH[10,3] 0.281 0.424 -0.737 0.345 0.848
beta0_pH[11,3] -0.242 0.447 -1.340 -0.209 0.509
beta0_pH[12,3] -3.408 0.475 -4.399 -3.396 -2.526
beta0_pH[13,3] 0.124 0.330 -0.589 0.140 0.721
beta0_pH[14,3] -0.467 0.269 -1.000 -0.460 0.041
beta0_pH[15,3] -0.618 0.381 -1.320 -0.645 0.290
beta0_pH[16,3] 0.112 0.279 -0.471 0.127 0.619
beta1_pH[1,1] 1.980 0.719 1.044 1.827 3.841
beta1_pH[2,1] 0.988 0.478 0.471 0.872 2.113
beta1_pH[3,1] 1.656 0.866 0.441 1.478 3.953
beta1_pH[4,1] 1.817 1.485 0.154 1.358 5.952
beta1_pH[5,1] 2.460 1.491 0.277 2.221 6.178
beta1_pH[6,1] 4.416 2.253 0.521 4.511 8.906
beta1_pH[7,1] 3.059 1.929 0.156 2.955 7.190
beta1_pH[8,1] 2.124 0.646 1.032 2.075 3.515
beta1_pH[9,1] 1.426 0.902 0.140 1.321 4.099
beta1_pH[10,1] 1.045 0.254 0.621 1.029 1.598
beta1_pH[11,1] 3.488 0.927 1.722 3.618 5.104
beta1_pH[12,1] 1.775 0.510 1.004 1.702 3.008
beta1_pH[13,1] 2.832 0.673 1.791 2.741 4.385
beta1_pH[14,1] 2.395 0.513 1.521 2.355 3.514
beta1_pH[15,1] 2.547 0.650 1.373 2.496 4.004
beta1_pH[16,1] 4.482 0.980 2.582 4.489 6.519
beta1_pH[1,2] 1.471 1.070 0.137 1.291 4.810
beta1_pH[2,2] 1.424 1.410 0.061 0.918 5.413
beta1_pH[3,2] 1.325 0.743 0.167 1.273 3.341
beta1_pH[4,2] 1.990 1.847 0.079 1.177 6.722
beta1_pH[5,2] 3.296 1.952 0.301 3.060 7.749
beta1_pH[6,2] 1.974 1.179 0.307 1.764 5.288
beta1_pH[7,2] 2.197 2.078 0.044 1.426 7.346
beta1_pH[8,2] 1.507 1.550 0.060 0.937 5.839
beta1_pH[9,2] 1.615 1.169 0.155 1.398 5.004
beta1_pH[10,2] 1.610 1.222 0.131 1.337 5.077
beta1_pH[11,2] 5.816 1.286 3.304 6.439 7.319
beta1_pH[12,2] 6.532 0.740 5.019 6.545 7.976
beta1_pH[13,2] 6.823 0.590 5.468 6.866 7.857
beta1_pH[14,2] 6.977 0.739 5.378 7.076 8.264
beta1_pH[15,2] 6.566 0.506 5.431 6.597 7.441
beta1_pH[16,2] 6.427 1.248 3.322 6.927 7.834
beta1_pH[1,3] 2.003 0.427 1.333 1.970 2.931
beta1_pH[2,3] 1.167 0.852 0.190 0.983 3.606
beta1_pH[3,3] 1.054 0.559 0.220 1.006 2.138
beta1_pH[4,3] 1.456 0.973 0.103 1.320 3.990
beta1_pH[5,3] 2.114 1.671 0.096 1.723 6.442
beta1_pH[6,3] 1.998 1.806 0.054 1.439 6.632
beta1_pH[7,3] 1.806 2.009 0.054 0.887 7.098
beta1_pH[8,3] 2.745 0.369 2.018 2.733 3.484
beta1_pH[9,3] 1.516 0.932 0.210 1.428 3.881
beta1_pH[10,3] 3.031 0.544 2.188 2.975 4.308
beta1_pH[11,3] 2.990 0.523 2.129 2.948 4.219
beta1_pH[12,3] 6.722 0.527 5.735 6.706 7.826
beta1_pH[13,3] 2.010 0.371 1.327 2.000 2.790
beta1_pH[14,3] 3.010 0.334 2.393 2.996 3.683
beta1_pH[15,3] 2.528 0.523 0.893 2.599 3.333
beta1_pH[16,3] 1.733 0.323 1.132 1.721 2.401
beta2_pH[1,1] 0.727 1.201 0.095 0.303 4.684
beta2_pH[2,1] 1.784 1.802 0.112 1.093 6.483
beta2_pH[3,1] 2.945 2.032 0.155 2.663 7.622
beta2_pH[4,1] 0.376 3.335 -6.151 0.576 6.975
beta2_pH[5,1] 2.589 2.382 -1.988 2.366 7.654
beta2_pH[6,1] 2.807 2.297 -0.525 2.470 7.871
beta2_pH[7,1] -0.571 3.709 -6.920 -0.933 6.760
beta2_pH[8,1] 2.319 1.969 0.189 1.749 7.153
beta2_pH[9,1] 2.310 2.741 -3.887 2.258 7.633
beta2_pH[10,1] 2.468 1.830 0.328 1.986 7.102
beta2_pH[11,1] 0.823 0.740 0.318 0.612 3.103
beta2_pH[12,1] 2.236 1.983 0.143 1.625 7.144
beta2_pH[13,1] 1.439 1.733 0.167 0.616 6.493
beta2_pH[14,1] 3.623 1.972 0.782 3.317 8.142
beta2_pH[15,1] 2.087 1.907 0.206 1.418 6.978
beta2_pH[16,1] 0.354 0.302 0.161 0.299 0.824
beta2_pH[1,2] 1.180 2.863 -5.691 1.456 6.143
beta2_pH[2,2] -1.592 2.850 -7.330 -1.328 4.396
beta2_pH[3,2] -2.584 2.294 -7.453 -2.334 2.356
beta2_pH[4,2] -2.746 2.488 -7.977 -2.600 2.264
beta2_pH[5,2] 0.748 2.840 -5.995 1.003 5.813
beta2_pH[6,2] -2.461 2.223 -7.385 -2.126 1.004
beta2_pH[7,2] -2.450 2.703 -7.785 -2.428 3.485
beta2_pH[8,2] -1.565 3.107 -7.591 -1.612 4.784
beta2_pH[9,2] -2.142 2.749 -7.408 -2.174 3.975
beta2_pH[10,2] -0.192 3.316 -7.034 0.238 6.046
beta2_pH[11,2] -2.518 4.078 -8.604 -4.001 3.921
beta2_pH[12,2] -1.591 1.273 -5.321 -1.133 -0.489
beta2_pH[13,2] -2.672 1.349 -6.443 -2.304 -1.097
beta2_pH[14,2] -3.512 1.624 -7.494 -3.166 -1.328
beta2_pH[15,2] -4.661 1.845 -8.751 -4.417 -1.614
beta2_pH[16,2] -2.950 4.216 -9.499 -4.410 5.316
beta2_pH[1,3] 2.879 1.799 0.383 2.576 7.227
beta2_pH[2,3] 1.518 2.229 -3.427 1.187 6.636
beta2_pH[3,3] -1.173 3.251 -6.945 -1.600 5.529
beta2_pH[4,3] 1.347 2.657 -4.652 1.303 6.535
beta2_pH[5,3] -0.084 3.071 -6.203 -0.117 5.940
beta2_pH[6,3] 0.289 3.213 -6.233 0.550 6.369
beta2_pH[7,3] -0.389 3.279 -6.706 -0.046 5.969
beta2_pH[8,3] 4.527 1.986 1.328 4.300 8.895
beta2_pH[9,3] 1.805 2.617 -4.683 1.811 6.812
beta2_pH[10,3] 1.536 1.409 0.351 1.004 5.718
beta2_pH[11,3] -1.405 1.018 -4.046 -1.170 -0.442
beta2_pH[12,3] -1.217 0.294 -1.915 -1.169 -0.768
beta2_pH[13,3] -2.641 1.516 -6.078 -2.335 -0.666
beta2_pH[14,3] -2.413 1.345 -5.934 -2.028 -0.890
beta2_pH[15,3] -1.663 1.760 -5.131 -1.587 3.000
beta2_pH[16,3] -2.525 1.559 -6.657 -2.140 -0.716
beta3_pH[1,1] 35.714 2.702 31.200 35.371 42.253
beta3_pH[2,1] 36.167 2.040 32.567 36.015 41.229
beta3_pH[3,1] 33.208 2.446 25.067 33.741 35.985
beta3_pH[4,1] 32.148 7.524 20.337 34.452 42.747
beta3_pH[5,1] 37.071 5.819 22.107 39.154 43.722
beta3_pH[6,1] 32.206 6.733 19.554 34.768 40.582
beta3_pH[7,1] 27.130 7.396 19.378 24.783 41.997
beta3_pH[8,1] 32.186 2.270 28.273 32.307 36.060
beta3_pH[9,1] 29.138 4.346 20.579 28.909 40.682
beta3_pH[10,1] 34.183 1.802 29.548 34.663 36.448
beta3_pH[11,1] 29.737 1.050 27.784 29.652 31.770
beta3_pH[12,1] 30.825 2.584 26.957 30.233 36.389
beta3_pH[13,1] 32.852 1.487 30.611 32.610 36.234
beta3_pH[14,1] 30.496 0.810 29.288 30.554 31.692
beta3_pH[15,1] 32.621 2.311 28.438 32.565 39.955
beta3_pH[16,1] 32.835 1.662 29.507 32.786 36.194
beta3_pH[1,2] 36.976 6.932 20.355 40.337 43.447
beta3_pH[2,2] 29.509 6.606 19.421 28.487 41.978
beta3_pH[3,2] 39.002 5.981 21.877 41.571 43.619
beta3_pH[4,2] 30.899 8.091 19.908 27.477 43.005
beta3_pH[5,2] 29.992 6.408 19.829 29.360 42.611
beta3_pH[6,2] 33.799 3.959 21.859 34.888 39.890
beta3_pH[7,2] 26.957 5.880 19.343 26.224 39.045
beta3_pH[8,2] 28.790 6.102 19.574 27.959 41.698
beta3_pH[9,2] 36.199 8.389 20.288 41.522 43.960
beta3_pH[10,2] 29.771 6.380 19.765 28.777 42.083
beta3_pH[11,2] 37.582 8.235 23.437 43.255 43.630
beta3_pH[12,2] 42.816 0.528 41.455 42.904 43.590
beta3_pH[13,2] 43.661 0.234 43.065 43.703 43.973
beta3_pH[14,2] 43.204 0.257 42.532 43.227 43.644
beta3_pH[15,2] 43.432 0.206 43.032 43.433 43.820
beta3_pH[16,2] 37.241 9.001 20.955 43.356 43.735
beta3_pH[1,3] 40.096 0.885 38.224 40.124 41.552
beta3_pH[2,3] 32.098 4.463 21.152 32.550 40.235
beta3_pH[3,3] 36.482 6.929 20.784 40.849 43.264
beta3_pH[4,3] 28.092 4.610 19.657 28.597 38.273
beta3_pH[5,3] 30.742 6.509 19.790 30.581 43.009
beta3_pH[6,3] 31.649 6.737 19.786 31.783 42.819
beta3_pH[7,3] 27.572 6.454 19.395 26.693 41.568
beta3_pH[8,3] 41.474 0.284 40.875 41.479 41.999
beta3_pH[9,3] 31.944 4.634 19.917 33.343 40.502
beta3_pH[10,3] 36.691 1.029 34.502 36.719 38.566
beta3_pH[11,3] 41.464 1.529 40.177 41.561 43.103
beta3_pH[12,3] 42.576 0.287 41.997 42.582 43.124
beta3_pH[13,3] 42.160 0.755 40.812 42.106 43.728
beta3_pH[14,3] 41.108 0.405 40.284 41.116 41.896
beta3_pH[15,3] 41.084 3.535 28.435 41.883 43.288
beta3_pH[16,3] 41.579 0.823 39.996 41.556 43.196
beta0_pelagic[1] 1.307 0.670 -0.023 1.370 2.317
beta0_pelagic[2] 1.132 0.380 0.148 1.251 1.607
beta0_pelagic[3] 0.171 0.265 -0.501 0.202 0.596
beta0_pelagic[4] 0.190 0.326 -0.594 0.226 0.708
beta0_pelagic[5] 0.508 0.516 -0.787 0.638 1.205
beta0_pelagic[6] 0.477 0.528 -0.851 0.562 1.225
beta0_pelagic[7] 1.484 0.161 1.164 1.487 1.782
beta0_pelagic[8] 1.623 0.252 1.061 1.655 1.937
beta0_pelagic[9] 1.773 0.568 0.409 1.919 2.521
beta0_pelagic[10] 2.170 0.570 0.540 2.371 2.784
beta0_pelagic[11] -0.873 0.556 -2.027 -0.871 0.043
beta0_pelagic[12] 1.644 0.144 1.360 1.644 1.928
beta0_pelagic[13] 0.210 0.289 -0.651 0.261 0.576
beta0_pelagic[14] -0.251 0.264 -0.857 -0.228 0.206
beta0_pelagic[15] -0.307 0.134 -0.565 -0.308 -0.048
beta0_pelagic[16] -0.245 0.406 -1.625 -0.179 0.285
beta1_pelagic[1] 1.177 0.926 0.051 1.021 3.961
beta1_pelagic[2] 0.543 0.613 0.018 0.329 2.557
beta1_pelagic[3] 0.916 0.369 0.403 0.838 1.845
beta1_pelagic[4] 1.040 0.353 0.476 0.994 1.944
beta1_pelagic[5] 0.649 0.688 0.018 0.447 2.299
beta1_pelagic[6] 1.325 0.675 0.407 1.211 3.250
beta1_pelagic[7] 2.140 1.952 0.103 1.321 6.989
beta1_pelagic[8] 1.116 1.438 0.022 0.506 5.223
beta1_pelagic[9] 1.455 0.730 0.486 1.281 3.408
beta1_pelagic[10] 0.803 0.951 0.023 0.431 3.525
beta1_pelagic[11] 4.381 1.006 2.641 4.251 6.406
beta1_pelagic[12] 3.036 0.325 2.413 3.032 3.695
beta1_pelagic[13] 2.443 0.599 1.637 2.352 4.080
beta1_pelagic[14] 4.010 0.625 2.925 3.959 5.355
beta1_pelagic[15] 2.432 0.240 1.980 2.425 2.900
beta1_pelagic[16] 3.896 0.798 2.724 3.792 6.162
beta2_pelagic[1] 1.911 2.139 -2.547 1.684 6.584
beta2_pelagic[2] 1.867 2.441 -3.155 1.493 6.897
beta2_pelagic[3] 1.563 1.686 0.103 0.868 6.196
beta2_pelagic[4] 2.072 1.646 0.212 1.594 6.361
beta2_pelagic[5] 0.504 3.235 -6.153 0.667 6.567
beta2_pelagic[6] 2.193 2.009 0.099 1.603 7.186
beta2_pelagic[7] -2.696 2.319 -8.420 -2.227 0.017
beta2_pelagic[8] -1.683 2.605 -6.896 -1.590 4.110
beta2_pelagic[9] 1.937 1.887 0.078 1.287 6.150
beta2_pelagic[10] 1.258 2.409 -4.086 0.845 6.623
beta2_pelagic[11] 0.155 0.053 0.086 0.145 0.285
beta2_pelagic[12] 1.036 0.387 0.528 0.973 1.872
beta2_pelagic[13] 0.652 0.609 0.132 0.494 2.276
beta2_pelagic[14] 0.298 0.098 0.167 0.279 0.554
beta2_pelagic[15] 1.905 0.938 0.850 1.658 4.575
beta2_pelagic[16] 0.336 0.175 0.118 0.290 0.834
beta3_pelagic[1] 24.695 4.215 19.795 23.032 35.796
beta3_pelagic[2] 28.310 5.103 19.939 28.409 37.911
beta3_pelagic[3] 30.200 2.780 24.622 30.233 36.191
beta3_pelagic[4] 25.790 1.978 22.128 25.825 30.282
beta3_pelagic[5] 28.240 4.831 20.646 27.747 38.128
beta3_pelagic[6] 30.446 3.346 24.994 30.336 37.554
beta3_pelagic[7] 26.683 3.642 19.804 27.053 33.061
beta3_pelagic[8] 26.594 4.742 20.207 26.120 37.073
beta3_pelagic[9] 31.818 3.833 23.022 32.842 37.116
beta3_pelagic[10] 28.006 5.077 19.408 27.989 38.105
beta3_pelagic[11] 37.478 2.609 31.885 37.667 41.753
beta3_pelagic[12] 41.887 0.123 41.558 41.926 41.997
beta3_pelagic[13] 40.804 1.073 38.012 41.089 41.953
beta3_pelagic[14] 40.651 0.995 38.289 40.850 41.945
beta3_pelagic[15] 41.848 0.144 41.460 41.890 41.995
beta3_pelagic[16] 40.815 1.088 37.899 41.128 41.959
mu_beta0_pelagic[1] 0.659 0.672 -0.658 0.644 1.973
mu_beta0_pelagic[2] 1.308 0.501 0.260 1.341 2.193
mu_beta0_pelagic[3] -0.002 0.621 -1.177 0.044 0.985
tau_beta0_pelagic[1] 6.332 14.275 0.070 1.722 58.636
tau_beta0_pelagic[2] 2.482 4.475 0.174 1.466 10.190
tau_beta0_pelagic[3] 1.325 1.004 0.143 1.073 3.792
beta0_yellow[1] -0.457 0.198 -0.924 -0.437 -0.131
beta0_yellow[2] 0.270 0.312 -0.549 0.346 0.675
beta0_yellow[3] -0.393 0.167 -0.754 -0.384 -0.096
beta0_yellow[4] 0.274 0.522 -0.807 0.339 1.064
beta0_yellow[5] -1.707 0.462 -2.576 -1.719 -0.759
beta0_yellow[6] 0.047 0.345 -0.590 0.069 0.649
beta0_yellow[7] 0.123 1.316 -2.941 0.625 1.559
beta0_yellow[8] 0.755 0.553 -0.956 0.891 1.307
beta0_yellow[9] -0.222 0.372 -0.911 -0.206 0.464
beta0_yellow[10] 0.613 0.187 0.258 0.610 0.995
beta0_yellow[11] -4.890 0.127 -4.999 -4.939 -4.550
beta0_yellow[12] -4.811 0.385 -4.998 -4.930 -3.964
beta0_yellow[13] -4.918 0.091 -4.999 -4.953 -4.669
beta0_yellow[14] -4.910 0.111 -4.999 -4.952 -4.596
beta0_yellow[15] -4.884 0.135 -4.999 -4.933 -4.505
beta0_yellow[16] -4.926 0.086 -4.999 -4.958 -4.691
beta1_yellow[1] 0.445 0.527 0.011 0.287 1.897
beta1_yellow[2] 1.515 0.703 0.759 1.287 3.485
beta1_yellow[3] 0.738 0.266 0.344 0.712 1.357
beta1_yellow[4] 2.639 1.177 0.937 2.506 5.149
beta1_yellow[5] 4.298 1.717 1.493 4.076 8.242
beta1_yellow[6] 3.249 1.681 0.804 2.896 7.188
beta1_yellow[7] 2.486 1.840 0.126 2.132 6.926
beta1_yellow[8] 1.888 1.594 0.098 1.424 6.150
beta1_yellow[9] 1.956 0.708 0.603 1.945 3.333
beta1_yellow[10] 2.443 0.541 1.460 2.405 3.562
beta1_yellow[11] 4.383 0.485 3.459 4.570 5.012
beta1_yellow[12] 6.096 2.000 3.171 6.952 8.755
beta1_yellow[13] 3.788 0.180 3.421 3.794 4.132
beta1_yellow[14] 4.704 0.200 4.270 4.717 5.063
beta1_yellow[15] 3.655 0.195 3.231 3.665 4.011
beta1_yellow[16] 4.592 0.184 4.219 4.596 4.947
beta2_yellow[1] -0.817 2.884 -6.324 -0.872 5.171
beta2_yellow[2] -1.175 1.383 -5.221 -0.659 -0.069
beta2_yellow[3] -2.319 1.781 -6.669 -1.892 -0.144
beta2_yellow[4] -0.365 0.741 -2.597 -0.142 -0.053
beta2_yellow[5] -3.258 1.810 -7.583 -2.937 -0.671
beta2_yellow[6] 2.991 1.891 0.234 2.724 7.154
beta2_yellow[7] 0.450 3.046 -6.019 0.643 5.995
beta2_yellow[8] -2.029 2.520 -7.333 -1.968 3.043
beta2_yellow[9] 2.667 1.923 0.020 2.402 6.814
beta2_yellow[10] -3.217 1.819 -7.471 -2.940 -0.638
beta2_yellow[11] -1.952 5.355 -8.658 -4.476 7.925
beta2_yellow[12] 1.386 2.256 -0.080 -0.027 6.832
beta2_yellow[13] -3.028 1.196 -6.011 -2.835 -1.386
beta2_yellow[14] -3.827 1.300 -7.076 -3.630 -1.918
beta2_yellow[15] -2.799 1.331 -6.059 -2.477 -1.084
beta2_yellow[16] -6.029 1.516 -9.264 -5.985 -3.387
beta3_yellow[1] 28.368 4.737 20.028 28.394 37.643
beta3_yellow[2] 29.338 2.234 24.428 29.286 34.092
beta3_yellow[3] 31.971 1.971 27.689 32.011 35.822
beta3_yellow[4] 29.866 3.711 22.345 29.988 36.857
beta3_yellow[5] 32.443 1.075 30.274 32.497 33.990
beta3_yellow[6] 38.414 2.383 29.657 38.780 41.011
beta3_yellow[7] 27.395 3.284 21.865 27.184 35.374
beta3_yellow[8] 29.085 3.863 21.351 28.946 36.599
beta3_yellow[9] 36.294 2.413 28.270 36.685 39.215
beta3_yellow[10] 29.187 0.715 27.479 29.291 30.211
beta3_yellow[11] 38.839 6.808 29.024 43.553 43.886
beta3_yellow[12] 32.574 3.588 29.034 31.554 41.200
beta3_yellow[13] 43.816 0.207 43.386 43.828 44.202
beta3_yellow[14] 43.762 0.211 43.356 43.764 44.168
beta3_yellow[15] 43.930 0.245 43.452 43.924 44.454
beta3_yellow[16] 43.621 0.149 43.323 43.623 43.900
mu_beta0_yellow[1] -0.078 0.409 -0.854 -0.082 0.734
mu_beta0_yellow[2] -0.072 0.579 -1.285 -0.052 1.058
mu_beta0_yellow[3] -5.285 0.457 -6.330 -5.229 -4.598
tau_beta0_yellow[1] 9.298 18.296 0.236 3.493 71.696
tau_beta0_yellow[2] 1.022 0.900 0.101 0.774 3.405
tau_beta0_yellow[3] 60.545 69.152 1.919 36.464 283.101
beta0_black[1] -0.097 0.148 -0.383 -0.100 0.191
beta0_black[2] 1.624 0.459 0.120 1.745 2.048
beta0_black[3] 1.183 0.250 0.605 1.225 1.514
beta0_black[4] 1.817 0.429 0.569 1.920 2.267
beta0_black[5] 1.393 1.636 -0.703 1.327 3.462
beta0_black[6] 1.373 1.742 -0.617 1.322 3.306
beta0_black[7] 1.382 1.591 -0.821 1.325 3.413
beta0_black[8] 1.117 0.299 0.420 1.161 1.592
beta0_black[9] 1.658 0.503 0.740 1.633 2.564
beta0_black[10] 1.354 0.142 1.073 1.358 1.622
beta0_black[11] 3.346 0.213 2.879 3.365 3.707
beta0_black[12] 4.403 0.178 4.056 4.401 4.765
beta0_black[13] -0.083 0.228 -0.549 -0.070 0.328
beta0_black[14] 1.753 0.660 0.132 1.938 2.592
beta0_black[15] 0.962 0.499 -0.472 1.081 1.487
beta0_black[16] 3.369 0.879 1.201 3.645 4.369
beta2_black[1] 3.151 1.734 0.826 2.769 7.504
beta2_black[2] -1.566 2.331 -6.526 -1.307 3.825
beta2_black[3] -0.058 3.077 -6.035 0.034 5.972
beta2_black[4] -2.115 1.985 -6.932 -1.537 -0.054
beta2_black[5] -0.008 3.164 -6.133 -0.031 6.196
beta2_black[6] -0.072 3.102 -6.138 -0.112 6.179
beta2_black[7] -0.043 3.103 -6.293 -0.008 5.993
beta2_black[8] -3.170 2.110 -7.817 -2.955 -0.044
beta2_black[9] -1.375 2.592 -6.487 -1.036 4.479
beta2_black[10] -0.637 2.951 -6.121 -0.883 5.676
beta2_black[11] -1.777 1.901 -5.760 -1.496 2.263
beta2_black[12] -3.149 1.692 -7.400 -2.827 -0.814
beta2_black[13] -2.123 1.530 -6.253 -1.656 -0.426
beta2_black[14] -0.827 1.227 -4.694 -0.312 -0.075
beta2_black[15] -1.586 1.866 -6.015 -1.087 0.765
beta2_black[16] 1.777 2.041 -2.404 1.436 6.207
beta3_black[1] 41.832 0.732 40.262 41.904 43.002
beta3_black[2] 29.898 8.031 19.217 30.684 44.529
beta3_black[3] 27.692 7.148 19.190 27.753 44.128
beta3_black[4] 32.898 3.531 22.654 32.865 39.418
beta3_black[5] 31.596 7.313 19.718 31.246 44.840
beta3_black[6] 31.761 7.262 19.790 31.647 44.733
beta3_black[7] 31.819 7.343 19.878 31.538 45.037
beta3_black[8] 28.693 7.857 20.268 23.296 42.863
beta3_black[9] 34.507 8.393 19.636 35.553 45.061
beta3_black[10] 29.720 9.887 19.418 25.069 45.523
beta3_black[11] 33.501 4.144 29.090 32.142 44.353
beta3_black[12] 32.881 0.571 31.529 32.949 33.796
beta3_black[13] 39.237 0.780 37.518 39.340 40.408
beta3_black[14] 37.958 3.692 30.028 38.311 45.044
beta3_black[15] 36.353 5.080 29.163 35.778 45.449
beta3_black[16] 33.805 4.191 29.128 32.511 43.934
beta4_black[1] -0.265 0.188 -0.629 -0.265 0.100
beta4_black[2] 0.276 0.172 -0.056 0.270 0.623
beta4_black[3] -0.990 0.180 -1.352 -0.994 -0.633
beta4_black[4] 0.634 0.215 0.219 0.631 1.071
beta4_black[5] 0.047 3.147 -6.029 0.123 6.316
beta4_black[6] 0.032 3.154 -6.164 0.065 6.251
beta4_black[7] -0.052 3.082 -6.039 -0.018 5.912
beta4_black[8] -0.831 0.374 -1.552 -0.836 -0.095
beta4_black[9] 2.116 1.123 0.238 2.002 4.682
beta4_black[10] 0.034 0.181 -0.311 0.035 0.389
beta4_black[11] -0.713 0.213 -1.123 -0.715 -0.303
beta4_black[12] 0.552 0.332 -0.095 0.552 1.204
beta4_black[13] -1.274 0.204 -1.668 -1.275 -0.867
beta4_black[14] -0.048 0.238 -0.506 -0.048 0.423
beta4_black[15] -0.938 0.212 -1.352 -0.941 -0.523
beta4_black[16] -0.600 0.231 -1.040 -0.599 -0.140
mu_beta0_black[1] 1.053 0.833 -0.544 1.112 2.385
mu_beta0_black[2] 1.310 0.606 0.058 1.326 2.337
mu_beta0_black[3] 1.949 1.177 -0.841 2.107 3.839
tau_beta0_black[1] 1.253 1.939 0.054 0.913 4.087
tau_beta0_black[2] 21.363 39.490 0.124 6.098 137.723
tau_beta0_black[3] 0.309 0.217 0.027 0.265 0.831
sigma_H[1] 0.226 0.048 0.141 0.222 0.328
sigma_H[2] 0.175 0.029 0.124 0.173 0.236
sigma_H[3] 0.186 0.041 0.110 0.184 0.273
sigma_H[4] 0.302 0.084 0.169 0.291 0.497
sigma_H[5] 1.027 0.213 0.630 1.019 1.455
sigma_H[6] 0.384 0.190 0.027 0.382 0.785
sigma_H[7] 0.293 0.058 0.202 0.286 0.427
sigma_H[8] 0.338 0.122 0.099 0.349 0.563
sigma_H[9] 0.525 0.127 0.328 0.508 0.809
sigma_H[10] 0.208 0.044 0.134 0.205 0.302
sigma_H[11] 0.270 0.045 0.196 0.267 0.370
sigma_H[12] 0.426 0.165 0.204 0.395 0.769
sigma_H[13] 0.217 0.037 0.151 0.215 0.299
sigma_H[14] 0.493 0.088 0.340 0.486 0.687
sigma_H[15] 0.247 0.039 0.180 0.242 0.334
sigma_H[16] 0.219 0.042 0.151 0.215 0.313
lambda_H[1] 3.522 4.688 0.171 1.965 16.015
lambda_H[2] 9.092 8.179 0.928 6.746 30.788
lambda_H[3] 6.419 8.964 0.301 3.543 30.761
lambda_H[4] 0.007 0.004 0.001 0.006 0.018
lambda_H[5] 2.212 5.645 0.020 0.502 16.788
lambda_H[6] 5.009 12.955 0.006 0.112 41.188
lambda_H[7] 0.016 0.011 0.003 0.014 0.044
lambda_H[8] 6.771 9.174 0.082 3.551 32.281
lambda_H[9] 0.017 0.011 0.003 0.014 0.046
lambda_H[10] 0.402 0.637 0.041 0.245 1.629
lambda_H[11] 0.238 0.390 0.011 0.111 1.172
lambda_H[12] 4.890 6.215 0.210 2.843 21.634
lambda_H[13] 3.674 3.233 0.243 2.798 12.180
lambda_H[14] 3.351 3.960 0.236 2.164 14.544
lambda_H[15] 0.024 0.036 0.004 0.016 0.091
lambda_H[16] 0.832 1.062 0.047 0.476 3.899
mu_lambda_H[1] 4.419 1.909 1.223 4.237 8.485
mu_lambda_H[2] 3.514 1.936 0.426 3.318 7.647
mu_lambda_H[3] 3.533 1.805 0.844 3.261 7.702
sigma_lambda_H[1] 8.794 4.264 2.160 8.247 18.402
sigma_lambda_H[2] 7.626 4.698 0.662 6.927 17.976
sigma_lambda_H[3] 6.336 3.950 1.174 5.413 16.372
beta_H[1,1] 6.943 1.081 4.296 7.115 8.514
beta_H[2,1] 9.873 0.469 8.859 9.902 10.743
beta_H[3,1] 7.987 0.749 6.145 8.092 9.154
beta_H[4,1] 10.629 7.602 -4.320 10.536 25.877
beta_H[5,1] -0.043 2.659 -5.669 0.088 4.931
beta_H[6,1] 2.307 4.448 -8.082 3.430 8.061
beta_H[7,1] 1.833 5.350 -9.366 2.255 11.116
beta_H[8,1] 1.336 4.124 -2.676 1.135 4.006
beta_H[9,1] 13.370 5.515 2.633 13.293 24.676
beta_H[10,1] 7.181 1.572 3.829 7.238 10.099
beta_H[11,1] 4.789 3.503 -3.137 5.451 9.789
beta_H[12,1] 2.609 1.028 0.752 2.544 4.864
beta_H[13,1] 9.090 0.833 7.266 9.134 10.473
beta_H[14,1] 2.177 1.056 0.232 2.194 4.184
beta_H[15,1] -6.283 3.636 -12.711 -6.550 1.604
beta_H[16,1] 3.261 2.562 -1.021 2.920 9.235
beta_H[1,2] 7.936 0.245 7.436 7.941 8.406
beta_H[2,2] 10.040 0.132 9.778 10.040 10.294
beta_H[3,2] 8.974 0.185 8.606 8.975 9.330
beta_H[4,2] 3.273 1.481 0.471 3.226 6.212
beta_H[5,2] 1.956 0.992 0.040 1.963 3.856
beta_H[6,2] 5.504 1.183 2.809 5.673 7.393
beta_H[7,2] 2.205 1.037 0.431 2.131 4.460
beta_H[8,2] 2.994 1.166 1.177 3.136 4.392
beta_H[9,2] 3.301 1.070 1.226 3.294 5.393
beta_H[10,2] 8.203 0.318 7.559 8.208 8.815
beta_H[11,2] 9.829 0.635 8.879 9.729 11.250
beta_H[12,2] 3.963 0.366 3.290 3.957 4.687
beta_H[13,2] 9.137 0.241 8.695 9.123 9.647
beta_H[14,2] 4.060 0.355 3.378 4.059 4.770
beta_H[15,2] 11.406 0.656 9.974 11.450 12.603
beta_H[16,2] 4.522 0.811 2.974 4.509 6.141
beta_H[1,3] 8.512 0.240 8.073 8.501 8.996
beta_H[2,3] 10.108 0.109 9.902 10.107 10.336
beta_H[3,3] 9.671 0.155 9.382 9.668 9.996
beta_H[4,3] -1.795 0.974 -3.581 -1.811 0.297
beta_H[5,3] 4.098 0.686 2.685 4.109 5.372
beta_H[6,3] 8.582 1.285 6.581 8.551 10.986
beta_H[7,3] -2.242 0.730 -3.718 -2.236 -0.866
beta_H[8,3] 5.413 0.561 4.698 5.317 6.542
beta_H[9,3] -2.510 0.764 -4.023 -2.501 -1.045
beta_H[10,3] 8.710 0.267 8.189 8.711 9.229
beta_H[11,3] 8.533 0.287 7.910 8.560 9.025
beta_H[12,3] 5.294 0.314 4.559 5.334 5.818
beta_H[13,3] 8.858 0.171 8.511 8.862 9.171
beta_H[14,3] 5.775 0.273 5.178 5.795 6.270
beta_H[15,3] 10.379 0.314 9.798 10.370 10.999
beta_H[16,3] 6.361 0.551 5.166 6.419 7.299
beta_H[1,4] 8.333 0.179 7.944 8.343 8.655
beta_H[2,4] 10.186 0.110 9.943 10.193 10.380
beta_H[3,4] 10.170 0.159 9.817 10.187 10.444
beta_H[4,4] 12.065 0.474 11.123 12.071 12.974
beta_H[5,4] 5.989 0.888 4.572 5.890 8.012
beta_H[6,4] 6.899 0.988 4.898 7.047 8.345
beta_H[7,4] 8.113 0.345 7.439 8.115 8.782
beta_H[8,4] 6.867 0.329 6.327 6.839 7.580
beta_H[9,4] 7.179 0.471 6.240 7.170 8.102
beta_H[10,4] 7.880 0.238 7.430 7.875 8.373
beta_H[11,4] 9.405 0.205 9.022 9.399 9.811
beta_H[12,4] 7.168 0.210 6.767 7.164 7.598
beta_H[13,4] 9.085 0.145 8.795 9.083 9.363
beta_H[14,4] 7.773 0.214 7.352 7.773 8.199
beta_H[15,4] 9.520 0.239 9.040 9.526 9.977
beta_H[16,4] 9.357 0.231 8.949 9.335 9.842
beta_H[1,5] 9.002 0.144 8.705 9.010 9.276
beta_H[2,5] 10.789 0.091 10.611 10.787 10.982
beta_H[3,5] 10.919 0.159 10.635 10.911 11.240
beta_H[4,5] 8.486 0.388 7.707 8.492 9.243
beta_H[5,5] 5.285 0.753 3.451 5.413 6.432
beta_H[6,5] 8.962 0.659 7.939 8.842 10.406
beta_H[7,5] 6.871 0.327 6.208 6.870 7.495
beta_H[8,5] 8.248 0.203 7.877 8.242 8.633
beta_H[9,5] 8.228 0.457 7.319 8.227 9.136
beta_H[10,5] 9.994 0.222 9.525 9.998 10.418
beta_H[11,5] 11.510 0.228 11.045 11.515 11.939
beta_H[12,5] 8.491 0.188 8.124 8.493 8.878
beta_H[13,5] 10.022 0.131 9.761 10.020 10.292
beta_H[14,5] 9.211 0.221 8.796 9.202 9.662
beta_H[15,5] 11.157 0.244 10.689 11.155 11.649
beta_H[16,5] 9.923 0.173 9.567 9.928 10.243
beta_H[1,6] 10.167 0.193 9.828 10.151 10.568
beta_H[2,6] 11.509 0.108 11.297 11.509 11.726
beta_H[3,6] 10.814 0.150 10.486 10.822 11.081
beta_H[4,6] 12.724 0.660 11.461 12.719 14.062
beta_H[5,6] 5.950 0.702 4.718 5.914 7.383
beta_H[6,6] 8.561 0.764 6.606 8.721 9.669
beta_H[7,6] 9.740 0.535 8.671 9.747 10.770
beta_H[8,6] 9.481 0.269 9.003 9.492 9.922
beta_H[9,6] 8.448 0.749 6.994 8.433 9.947
beta_H[10,6] 9.589 0.297 8.942 9.611 10.102
beta_H[11,6] 10.820 0.354 10.068 10.843 11.479
beta_H[12,6] 9.368 0.240 8.897 9.364 9.874
beta_H[13,6] 11.041 0.159 10.752 11.032 11.366
beta_H[14,6] 9.833 0.282 9.270 9.834 10.391
beta_H[15,6] 10.852 0.429 9.995 10.855 11.698
beta_H[16,6] 10.547 0.235 10.054 10.558 10.984
beta_H[1,7] 10.953 0.828 9.025 11.022 12.395
beta_H[2,7] 12.196 0.412 11.349 12.200 13.025
beta_H[3,7] 10.564 0.621 9.206 10.629 11.596
beta_H[4,7] 2.934 3.296 -3.591 2.999 9.407
beta_H[5,7] 6.594 2.376 2.465 6.434 12.133
beta_H[6,7] 9.667 2.919 4.355 9.399 17.225
beta_H[7,7] 10.984 2.685 5.607 11.025 16.224
beta_H[8,7] 10.935 1.077 9.345 10.861 12.950
beta_H[9,7] 4.578 3.930 -3.003 4.637 12.174
beta_H[10,7] 9.663 1.340 7.076 9.615 12.433
beta_H[11,7] 11.040 1.737 7.741 10.976 14.732
beta_H[12,7] 9.999 0.887 7.928 10.079 11.493
beta_H[13,7] 11.656 0.722 9.955 11.753 12.767
beta_H[14,7] 10.427 0.911 8.469 10.498 12.025
beta_H[15,7] 12.091 2.229 7.729 12.114 16.475
beta_H[16,7] 12.332 1.256 10.329 12.165 15.278
beta0_H[1] 8.796 13.271 -16.933 9.070 34.288
beta0_H[2] 10.756 6.045 -1.774 10.772 22.538
beta0_H[3] 9.898 9.276 -9.476 10.151 28.311
beta0_H[4] 8.922 176.262 -337.503 6.507 346.846
beta0_H[5] 4.812 33.032 -60.166 4.044 74.102
beta0_H[6] 7.168 58.120 -121.866 7.791 142.385
beta0_H[7] 6.012 122.879 -242.570 6.058 242.854
beta0_H[8] 6.938 37.374 -20.159 6.428 34.998
beta0_H[9] 5.872 118.227 -229.332 4.551 244.681
beta0_H[10] 8.956 29.253 -50.223 8.538 72.337
beta0_H[11] 9.941 51.082 -97.157 9.586 122.420
beta0_H[12] 6.744 11.312 -13.653 6.777 29.674
beta0_H[13] 9.713 9.932 -9.886 9.683 29.258
beta0_H[14] 7.358 11.561 -14.721 6.998 30.176
beta0_H[15] 8.464 103.501 -197.608 9.510 216.062
beta0_H[16] 8.281 24.246 -38.751 7.884 59.718